Add AVX512 optimizations for matrix multiply
diff --git a/Eigen/Core b/Eigen/Core
index 7bbdee3..141460d 100644
--- a/Eigen/Core
+++ b/Eigen/Core
@@ -191,6 +191,7 @@
#include "src/Core/arch/AVX/MathFunctions.h"
#include "src/Core/arch/AVX512/MathFunctions.h"
#include "src/Core/arch/AVX512/TrsmKernel.h"
+ #include "src/Core/arch/AVX512/GemmKernel.h"
#elif defined EIGEN_VECTORIZE_AVX
// Use AVX for floats and doubles, SSE for integers
#include "src/Core/arch/SSE/PacketMath.h"
diff --git a/Eigen/src/Core/arch/AVX512/GemmKernel.h b/Eigen/src/Core/arch/AVX512/GemmKernel.h
new file mode 100644
index 0000000..4b2df9d
--- /dev/null
+++ b/Eigen/src/Core/arch/AVX512/GemmKernel.h
@@ -0,0 +1,973 @@
+#ifndef GEMM_KERNEL_H
+#define GEMM_KERNEL_H
+
+#include <x86intrin.h>
+#include <immintrin.h>
+#include <type_traits>
+
+#define SECOND_FETCH (32)
+
+#if (EIGEN_COMP_GNUC_STRICT != 0) && !defined(EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_A_REGS)
+// Use less registers to load A elements to workaround compiler spills. Loose a
+// bit of performance (less than ~2%).
+#define EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_A_REGS
+#endif
+
+namespace Eigen {
+namespace internal {
+
+static inline constexpr int div_up(int a, int b) {
+ return (a + b - 1) / b;
+}
+
+template <typename Scalar>
+class gemm_class
+{
+ using vec = typename std::conditional<std::is_same<Scalar, float>::value,
+ Packet16f, Packet8d>::type;
+ using vec_ymm = typename std::conditional<std::is_same<Scalar, float>::value,
+ Packet8f, Packet4d>::type;
+ using vec_xmm = typename std::conditional<std::is_same<Scalar, float>::value,
+ Packet4f, Packet2d>::type;
+
+ static constexpr bool is_f32 = sizeof(Scalar) == sizeof(float);
+ static constexpr bool is_f64 = sizeof(Scalar) == sizeof(double);
+
+#ifndef EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_A_REGS
+ static constexpr int a_regs[] = {0, 1, 2, 3, 4, 5};
+#else
+ static constexpr int a_regs[] = {0, 1, 2, 0, 1, 2};
+#endif
+#ifndef EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_B_REGS
+ static constexpr int b_regs[] = {6, 7};
+#else
+ static constexpr int b_regs[] = {6, 6};
+#endif
+ static constexpr int c_regs[] = {
+ 8 , 16, 24,
+ 9 , 17, 25,
+ 10, 18, 26,
+ 11, 19, 27,
+ 12, 20, 28,
+ 13, 21, 29,
+ 14, 22, 30,
+ 15, 23, 31,
+ };
+
+ static constexpr int a_shift = 128;
+ static constexpr int b_shift = 128;
+
+ static constexpr int nelems_in_cache_line = is_f32 ? 16 : 8;
+ static constexpr int a_prefetch_size = nelems_in_cache_line * 2;
+ static constexpr int b_prefetch_size = nelems_in_cache_line * 8;
+
+ vec zmm[32];
+
+ // gemm arguments.
+ int64_t m;
+ const int64_t n, k, ldc;
+ const Scalar *alpha;
+
+ const Scalar *a, *b;
+ Scalar *c;
+
+ const bool is_alpha1;
+ const bool is_beta0;
+
+ const int64_t a_stride, b_stride;
+ const int64_t a_off, b_off;
+
+public:
+ EIGEN_ALWAYS_INLINE void prefetch_a(const Scalar *a_addr)
+ {
+ _mm_prefetch((char *) (a_prefetch_size + a_addr - a_shift), _MM_HINT_T0);
+ }
+
+ EIGEN_ALWAYS_INLINE void prefetch_b(const Scalar *b_addr)
+ {
+ _mm_prefetch((char *) (b_prefetch_size + b_addr - b_shift), _MM_HINT_T0);
+ }
+
+ EIGEN_ALWAYS_INLINE void prefetch_x(const Scalar *x_addr)
+ {
+ _mm_prefetch((char *) (x_addr - a_shift), _MM_HINT_T2);
+ }
+
+ EIGEN_ALWAYS_INLINE void prefetch_c(const Scalar *c_addr)
+ {
+#if defined(__PRFCHW__) && __PRFCHW__ == 1
+ _m_prefetchw((void *) c_addr);
+#else
+ _mm_prefetch((char *) c_addr, _MM_HINT_T0);
+#endif
+ }
+
+ template <int nelems>
+ EIGEN_ALWAYS_INLINE void a_load(vec &a_reg, const Scalar *a_addr)
+ {
+ switch (nelems * sizeof(*a_addr) * 8) {
+ default:
+ case 512 * 3: a_reg = ploadu<vec>(a_addr); break;
+ case 512 * 2: a_reg = ploadu<vec>(a_addr); break;
+ case 512 * 1: a_reg = ploadu<vec>(a_addr); break;
+ case 256 * 1: a_reg = preinterpret<vec>(_mm512_broadcast_f64x4(ploadu<Packet4d>(reinterpret_cast<const double *>(a_addr)))); break;
+ case 128 * 1: a_reg = preinterpret<vec>(_mm512_broadcast_f32x4(ploadu<Packet4f>(reinterpret_cast<const float *>(a_addr)))); break;
+ case 64 * 1: a_reg = preinterpret<vec>(pload1<Packet8d>(reinterpret_cast<const double *>(a_addr))); break;
+ case 32 * 1: a_reg = pload1<vec>(a_addr); break;
+ }
+ }
+
+ EIGEN_ALWAYS_INLINE void b_load(vec &b_reg, const Scalar *b_addr)
+ {
+ b_reg = pload1<vec>(b_addr);
+ }
+
+ template <int nelems>
+ EIGEN_ALWAYS_INLINE void c_store(Scalar *mem, vec &src)
+ {
+ switch (nelems * sizeof(*mem) * 8) {
+ default:
+ case 512 * 3: pstoreu(mem, src); break;
+ case 512 * 2: pstoreu(mem, src); break;
+ case 512 * 1: pstoreu(mem, src); break;
+ case 256 * 1: pstoreu(mem, preinterpret<vec_ymm>(src)); break;
+ case 128 * 1: pstoreu(mem, preinterpret<vec_xmm>(src)); break;
+ case 64 * 1: pstorel(mem, preinterpret<vec_xmm>(src)); break;
+ case 32 * 1: pstores(mem, preinterpret<vec_xmm>(src)); break;
+ }
+ }
+
+ template <int nelems>
+ EIGEN_ALWAYS_INLINE void vaddm(vec &dst, const Scalar *mem, vec &src)
+ {
+ switch (nelems * sizeof(*mem) * 8) {
+ default:
+ case 512 * 3: dst = padd(src, ploadu<vec>(mem)); break;
+ case 512 * 2: dst = padd(src, ploadu<vec>(mem)); break;
+ case 512 * 1: dst = padd(src, ploadu<vec>(mem)); break;
+ case 256 * 1: dst = preinterpret<vec>(padd(preinterpret<vec_ymm>(src), ploadu<vec_ymm>(mem))); break;
+ case 128 * 1: dst = preinterpret<vec>(padd(preinterpret<vec_xmm>(src), ploadu<vec_xmm>(mem))); break;
+ case 64 * 1: dst = preinterpret<vec>(padd(preinterpret<vec_xmm>(src), ploadl<vec_xmm>(mem))); break;
+ case 32 * 1: dst = preinterpret<vec>(padds(preinterpret<vec_xmm>(src), ploads<vec_xmm>(mem))); break;
+ }
+ }
+
+ EIGEN_STRONG_INLINE void vfmadd(vec &dst, const vec &src1, const vec &src2) {
+ dst = pmadd(src1, src2, dst);
+
+#if (EIGEN_COMP_GNUC != 0) || (EIGEN_COMP_CLANG != 0)
+ // Workaround register spills for gcc and clang
+ __asm__ ("#" : [dst] "+v" (dst) : [src1] "%v" (src1), [src2] "v" (src2));
+#endif
+ }
+
+ template <int nelems>
+ EIGEN_ALWAYS_INLINE void vfmaddm(vec &dst, const Scalar *mem, vec &src, vec &scale)
+ {
+ switch (nelems * sizeof(*mem) * 8) {
+ default:
+ case 512 * 3: dst = pmadd(scale, src, ploadu<vec>(mem)); break;
+ case 512 * 2: dst = pmadd(scale, src, ploadu<vec>(mem)); break;
+ case 512 * 1: dst = pmadd(scale, src, ploadu<vec>(mem)); break;
+ case 256 * 1: dst = preinterpret<vec>(pmadd(preinterpret<vec_ymm>(scale), preinterpret<vec_ymm>(src), ploadu<vec_ymm>(mem))); break;
+ case 128 * 1: dst = preinterpret<vec>(pmadd(preinterpret<vec_xmm>(scale), preinterpret<vec_xmm>(src), ploadu<vec_xmm>(mem))); break;
+ case 64 * 1: dst = preinterpret<vec>(pmadd(preinterpret<vec_xmm>(scale), preinterpret<vec_xmm>(src), ploadl<vec_xmm>(mem))); break;
+ case 32 * 1: dst = preinterpret<vec>(pmadds(preinterpret<vec_xmm>(scale), preinterpret<vec_xmm>(src), ploads<vec_xmm>(mem))); break;
+ }
+ }
+
+ gemm_class(int64_t m_, int64_t n_, int64_t k_, int64_t ldc_, const Scalar *alpha_,
+ const Scalar *a_, const Scalar *b_, Scalar *c_,
+ bool is_alpha1_, bool is_beta0_,
+ int64_t a_stride_, int64_t b_stride_,
+ int64_t a_off_, int64_t b_off_)
+ : m(m_)
+ , n(n_)
+ , k(k_)
+ , ldc(ldc_)
+ , alpha(alpha_)
+ , a(a_)
+ , b(b_)
+ , c(c_)
+ , is_alpha1(is_alpha1_)
+ , is_beta0(is_beta0_)
+ , a_stride(a_stride_)
+ , b_stride(b_stride_)
+ , a_off(a_off_)
+ , b_off(b_off_)
+ {
+
+ // Zero out all accumulation registers.
+ zmm[8 ] = pzero(zmm[8 ]);
+ zmm[9 ] = pzero(zmm[9 ]);
+ zmm[10] = pzero(zmm[10]);
+ zmm[11] = pzero(zmm[11]);
+ zmm[12] = pzero(zmm[12]);
+ zmm[13] = pzero(zmm[13]);
+ zmm[14] = pzero(zmm[14]);
+ zmm[15] = pzero(zmm[15]);
+ zmm[16] = pzero(zmm[16]);
+ zmm[17] = pzero(zmm[17]);
+ zmm[18] = pzero(zmm[18]);
+ zmm[19] = pzero(zmm[19]);
+ zmm[20] = pzero(zmm[20]);
+ zmm[21] = pzero(zmm[21]);
+ zmm[22] = pzero(zmm[22]);
+ zmm[23] = pzero(zmm[23]);
+ zmm[24] = pzero(zmm[24]);
+ zmm[25] = pzero(zmm[25]);
+ zmm[26] = pzero(zmm[26]);
+ zmm[27] = pzero(zmm[27]);
+ zmm[28] = pzero(zmm[28]);
+ zmm[29] = pzero(zmm[29]);
+ zmm[30] = pzero(zmm[30]);
+ zmm[31] = pzero(zmm[31]);
+ }
+
+ template <int j, int endX, int i, int endY, int nelems>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(j > endX) || (i > endY)>
+ a_loads(const Scalar *ao)
+ {
+ EIGEN_UNUSED_VARIABLE(ao);
+ }
+
+ template <int j, int endX, int i, int endY, int nelems>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(j <= endX) && (i <= endY)>
+ a_loads(const Scalar *ao)
+ {
+ if (j < endX) {
+ if (i < endY) {
+ auto &a_reg = zmm[a_regs[i + (j % 2) * 3]];
+ const Scalar *a_addr = ao + nelems * j + nelems_in_cache_line * i - a_shift;
+ a_load<nelems>(a_reg, a_addr);
+
+ a_loads<j, endX, i + 1, endY, nelems>(ao);
+ } else {
+ a_loads<j + 1, endX, 0, endY, nelems>(ao);
+ }
+ }
+ }
+
+ template <int un, int max_b_unroll, int i, int um_vecs, int a_unroll, int b_unroll>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(un > max_b_unroll) || (i > um_vecs)>
+ prefetch_cs(const Scalar *co1, const Scalar *co2)
+ {
+ EIGEN_UNUSED_VARIABLE(co1);
+ EIGEN_UNUSED_VARIABLE(co2);
+ }
+
+ /* C prefetch loop structure.
+ * for (int un = 0; un < 8; un++) {
+ * if (b_unroll >= un + 1) {
+ * if (un == 4) co2 = co1 + 4 * ldc;
+ *
+ * for (int i = 0; i < um_vecs; i++) {
+ * Scalar *co = (un + 1 <= 4) ? co1 : co2;
+ * auto co_off = (un % 4) * ldc + a_unroll - 1 + i * nelems_in_cache_line * sizeof *co;
+ * prefetch_c(co + co_off);
+ * }
+ * }
+ * }
+ */
+
+ template <int un, int max_b_unroll, int i, int um_vecs, int a_unroll, int b_unroll>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(un <= max_b_unroll) && (i <= um_vecs)>
+ prefetch_cs(Scalar *&co1, Scalar *&co2)
+ {
+ if (un < max_b_unroll) {
+
+ if (b_unroll >= un + 1) {
+ if (un == 4 && i == 0) co2 = co1 + 4 * ldc;
+
+ if (i < um_vecs) {
+ Scalar *co = (un + 1 <= 4) ? co1 : co2;
+ auto co_off = (un % 4) * ldc + a_unroll - 1 + i * nelems_in_cache_line * sizeof *co;
+ prefetch_c(co + co_off);
+
+ prefetch_cs<un, max_b_unroll, i + 1, um_vecs, a_unroll, b_unroll>(co1, co2);
+ } else {
+ prefetch_cs<un + 1, max_b_unroll, 0, um_vecs, a_unroll, b_unroll>(co1, co2);
+ }
+
+ } else {
+ prefetch_cs<un + 1, max_b_unroll, 0, um_vecs, a_unroll, b_unroll>(co1, co2);
+ }
+ }
+ }
+
+ // load_c
+ template <int i, int um_vecs, int idx, int nelems>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(i > um_vecs)>
+ scale_load_c(const Scalar *cox, vec &alpha_reg)
+ {
+ EIGEN_UNUSED_VARIABLE(cox);
+ EIGEN_UNUSED_VARIABLE(alpha_reg);
+ }
+
+ template <int i, int um_vecs, int idx, int nelems>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(i <= um_vecs)>
+ scale_load_c(const Scalar *cox, vec &alpha_reg)
+ {
+
+ if (i < um_vecs) {
+ auto &c_reg = zmm[c_regs[i + idx * 3]];
+ auto c_mem = cox + i * nelems_in_cache_line;
+
+ if (!is_beta0 && is_alpha1)
+ vaddm<nelems>(c_reg, c_mem, c_reg);
+ else if (!is_beta0 && !is_alpha1)
+ vfmaddm<nelems>(c_reg, c_mem, c_reg, alpha_reg);
+ else if (is_beta0 && !is_alpha1)
+ c_reg = pmul(alpha_reg, c_reg);
+
+ scale_load_c<i + 1, um_vecs, idx, nelems>(cox, alpha_reg);
+ }
+ }
+
+ // store_c
+ template <int i, int um_vecs, int idx, int nelems>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(i > um_vecs)>
+ write_c(Scalar *cox)
+ {
+ EIGEN_UNUSED_VARIABLE(cox);
+ }
+
+ template <int i, int um_vecs, int idx, int nelems>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(i <= um_vecs)>
+ write_c(Scalar *cox)
+ {
+ if (i < um_vecs) {
+ auto &c_reg = zmm[c_regs[i + idx * 3]];
+ auto c_mem = cox + i * nelems_in_cache_line;
+
+ c_store<nelems>(c_mem, c_reg);
+ c_reg = pzero(c_reg);
+
+ write_c<i + 1, um_vecs, idx, nelems>(cox);
+ }
+ }
+
+ // update c matrix
+ template <int pow, int max_b_unroll, int count, int a_unroll, int b_unroll, int idx>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(pow > (max_b_unroll << 1)) || (count > (pow + 1) / 2 + 1)>
+ c_update(Scalar *&co1, Scalar *&co2)
+ {
+ EIGEN_UNUSED_VARIABLE(co1);
+ EIGEN_UNUSED_VARIABLE(co2);
+ }
+
+ /* C update loop structure.
+ * co2 = co1 + ldc;
+ *
+ * auto &alpha_reg = zmm[0];
+ * if (!is_alpha1) alpha_reg = pload1<vec>(alpha);
+ *
+ * int idx = 0;
+ * for (pow = 1; pow <= 8; pow <<= 1) {
+ *
+ * if (b_unroll >= pow) {
+ * for (count = 1; count < (pow + 1) / 2 + 1; count++) {
+ * if (pow >= 4) co2 += ldc;
+ *
+ * const Scalar *cox = (idx == 0) ? co1 : co2;
+ *
+ * const int um_vecs = div_up(a_unroll, nelems_in_cache_line);
+ * scale_load_c<0, um_vecs, idx, a_unroll>(cox, alpha_reg);
+ * write_c<0, um_vecs, idx, a_unroll>(cox);
+ *
+ * idx++;
+ * }
+ * }
+ * }
+ *
+ * if (b_unroll == 1)
+ * co1 += ldc;
+ * else
+ * co1 = co2 + ldc;
+ */
+
+ template <int pow, int max_b_unroll, int count, int a_unroll, int b_unroll, int idx>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(pow <= (max_b_unroll << 1)) && (count <= (pow + 1) / 2 + 1)>
+ c_update(Scalar *&co1, Scalar *&co2)
+ {
+ const bool first_call = idx == 0;
+ auto &alpha_reg = zmm[0];
+
+ if (first_call) {
+ co2 = co1 + ldc;
+ if (!is_alpha1) alpha_reg = pload1<vec>(alpha);
+ }
+
+ if (pow < (max_b_unroll << 1) && pow <= b_unroll) {
+ if (count < (pow + 1) / 2 + 1) {
+ if (pow >= 4) co2 += ldc;
+
+ Scalar *cox = idx == 0 ? co1 : co2;
+
+ const int um_vecs = div_up(a_unroll, nelems_in_cache_line);
+ scale_load_c<0, um_vecs, idx, a_unroll>(cox, alpha_reg);
+ write_c<0, um_vecs, idx, a_unroll>(cox);
+
+ // Go to the next count and next idx.
+ c_update<pow, max_b_unroll, count + 1, a_unroll, b_unroll, idx + 1>(co1, co2);
+ } else {
+ // Go to the next pow and reset count.
+ c_update<pow << 1, max_b_unroll, 1, a_unroll, b_unroll, idx>(co1, co2);
+ }
+ } else {
+ if (b_unroll == 1)
+ co1 += ldc;
+ else
+ co1 = co2 + ldc;
+ }
+ }
+
+ // compute
+ template <int um, int um_vecs, int idx, int uk, bool fetch_x, bool ktail>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(um > um_vecs)>
+ compute(const Scalar *ao, const Scalar *bo, int &fetchA_idx, int &fetchB_idx, vec &b_reg)
+ {
+ EIGEN_UNUSED_VARIABLE(ao);
+ EIGEN_UNUSED_VARIABLE(bo);
+ EIGEN_UNUSED_VARIABLE(fetchA_idx);
+ EIGEN_UNUSED_VARIABLE(fetchB_idx);
+ EIGEN_UNUSED_VARIABLE(b_reg);
+ }
+
+ template <int um, int um_vecs, int idx, int uk, bool fetch_x, bool ktail>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(um <= um_vecs)>
+ compute(const Scalar *ao, const Scalar *bo, int &fetchA_idx, int &fetchB_idx, vec &b_reg)
+ {
+ if (um < um_vecs) {
+ auto &c_reg = zmm[c_regs[um + idx * 3]];
+ auto &a_reg = zmm[a_regs[um + (uk % 2) * 3]];
+
+ vfmadd(c_reg, a_reg, b_reg);
+
+ if (!fetch_x && um == 0 && (((idx == 0 || idx == 6) && (uk % 2 == 0 || is_f64 || ktail)) || (idx == 3 && (uk % 2 == 1 || is_f64 || ktail)))) {
+ prefetch_a(ao + nelems_in_cache_line * fetchA_idx);
+ fetchA_idx++;
+ }
+
+ if (um == 0 && idx == 1 && (uk % 2 == 0 || is_f64 || ktail)) {
+ prefetch_b(bo + nelems_in_cache_line * fetchB_idx);
+ fetchB_idx++;
+ }
+
+ compute<um + 1, um_vecs, idx, uk, fetch_x, ktail>(ao, bo, fetchA_idx, fetchB_idx, b_reg);
+ }
+ }
+
+ // load_a
+ template <int um, int um_vecs, int uk, int nelems, bool ktail>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(um > um_vecs)>
+ load_a(const Scalar *ao)
+ {
+ EIGEN_UNUSED_VARIABLE(ao);
+ }
+
+ template <int um, int um_vecs, int uk, int nelems, bool ktail>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(um <= um_vecs)>
+ load_a(const Scalar *ao)
+ {
+ if (um < um_vecs) {
+ auto &a_reg = zmm[a_regs[um + (uk % 2) * 3]];
+#ifndef EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_A_REGS
+ const Scalar *a_addr = ao + nelems * (1 + !ktail + uk) + nelems_in_cache_line * um - a_shift;
+#else
+ const Scalar *a_addr = ao + nelems * (1 + uk) + nelems_in_cache_line * um - a_shift;
+#endif
+ a_load<nelems>(a_reg, a_addr);
+
+ load_a<um + 1, um_vecs, uk, nelems, ktail>(ao);
+ }
+ }
+ template<int uk, int pow, int count, int um_vecs, int b_unroll, bool ktail, bool fetch_x, bool c_fetch>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(count > (pow + 1) / 2)>
+ innerkernel_1pow(const Scalar *&aa, const Scalar * const &ao, const Scalar * const &bo, Scalar *&co2, int &fetchA_idx, int &fetchB_idx)
+ {
+ EIGEN_UNUSED_VARIABLE(aa);
+ EIGEN_UNUSED_VARIABLE(ao);
+ EIGEN_UNUSED_VARIABLE(bo);
+ EIGEN_UNUSED_VARIABLE(co2);
+ EIGEN_UNUSED_VARIABLE(fetchA_idx);
+ EIGEN_UNUSED_VARIABLE(fetchB_idx);
+ }
+
+ template<int uk, int pow, int count, int um_vecs, int b_unroll, bool ktail, bool fetch_x, bool c_fetch>
+ EIGEN_ALWAYS_INLINE std::enable_if_t<(count <= (pow + 1) / 2)>
+ innerkernel_1pow(const Scalar *&aa, const Scalar * const &ao, const Scalar * const &bo, Scalar *&co2, int &fetchA_idx, int &fetchB_idx)
+ {
+ const int idx = (pow / 2) + count;
+
+ if (count < (pow + 1) / 2) {
+ auto &b_reg = zmm[b_regs[idx % 2]];
+
+ if (fetch_x && uk == 3 && idx == 0) prefetch_x(aa);
+ if (fetch_x && uk == 3 && idx == 4) aa += 8;
+
+ if (b_unroll >= pow) {
+
+ compute<0, um_vecs, idx, uk, fetch_x, ktail>(ao, bo, fetchA_idx, fetchB_idx, b_reg);
+
+#ifndef EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_B_REGS
+ const Scalar *b_addr = bo + b_unroll * uk + idx + 1 + (b_unroll > 1) - b_shift;
+#else
+ const Scalar *b_addr = bo + b_unroll * uk + idx + 1 - b_shift;
+#endif
+ b_load(b_reg, b_addr);
+ }
+
+ // Go to the next count.
+ innerkernel_1pow<uk, pow, count + 1, um_vecs, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+
+ } else {
+ // Maybe prefetch C data after count-loop.
+ if (pow == 2 && c_fetch) {
+ if (uk % 3 == 0 && uk > 0) {
+ co2 += ldc;
+ } else {
+ prefetch_c(co2 + (uk % 3) * nelems_in_cache_line);
+ }
+ }
+ }
+ }
+
+ template<int uk, int max_b_unroll, int a_unroll, int b_unroll, bool ktail, bool fetch_x, bool c_fetch>
+ EIGEN_ALWAYS_INLINE void innerkernel_1uk(const Scalar *&aa, const Scalar * const &ao, const Scalar * const &bo, Scalar *&co2, int &fetchA_idx, int &fetchB_idx)
+ {
+ const int um_vecs = div_up(a_unroll, nelems_in_cache_line);
+
+ if (max_b_unroll >= 1) innerkernel_1pow<uk, 1, 0, um_vecs, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+ if (max_b_unroll >= 2) innerkernel_1pow<uk, 2, 0, um_vecs, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+ if (max_b_unroll >= 4) innerkernel_1pow<uk, 4, 0, um_vecs, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+ if (max_b_unroll >= 8) innerkernel_1pow<uk, 8, 0, um_vecs, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+
+ // Load A after pow-loop.
+ load_a<0, um_vecs, uk, a_unroll, ktail>(ao);
+ }
+
+ /* Inner kernel loop structure.
+ * for (int uk = 0; uk < kfactor; uk++) {
+ * int idx = 0;
+ *
+ * for (pow = 1; pow < max_b_unroll << 1; pow <<= 1) {
+ * for (int count = 0; count < (pow + 1) / 2; count++) {
+ * auto &b_reg = zmm[b_regs[idx % 2]];
+ *
+ * if (fetch_x && uk == 3 && idx == 0) prefetch_x(aa);
+ * if (fetch_x && uk == 3 && idx == 4) aa += 8;
+ *
+ * if (b_unroll >= pow) {
+ * compute<0, um_vecs, idx, uk, fetchx, ktail>(ao, bo, fetchA_idx, fetchB_idx, b_reg);
+ *
+ * const Scalar *b_addr = bo + b_unroll * uk + idx + 1 + (b_unroll > 1) - b_shift ;
+ * b_load(b_reg, b_addr);
+ * }
+ * idx++;
+ * }
+ *
+ * Maybe prefetch C data.
+ * if (pow == 2 && c_fetch) {
+ * if (uk % 3 == 0 && uk > 0) {
+ * co2 += ldc;
+ * } else {
+ * prefetch_c(co2 + (uk % 3) * nelems_in_cache_line);
+ * }
+ * }
+ * }
+ *
+ * Load A.
+ * load_a<0, um_vecs, uk, ktail, a_unroll>(ao);
+ * }
+ *
+ * Advance A/B pointers after uk-loop.
+ * ao += a_unroll * kfactor;
+ * bo += b_unroll * kfactor;
+ */
+
+ template <int a_unroll, int b_unroll, int k_factor, int max_b_unroll, int max_k_factor, bool c_fetch>
+ EIGEN_ALWAYS_INLINE void innerkernel(const Scalar *&aa, const Scalar *&ao, const Scalar *&bo, Scalar *&co2)
+ {
+ int fetchA_idx = 0;
+ int fetchB_idx = 0;
+
+ const bool fetch_x = k_factor == max_k_factor;
+ const bool ktail = k_factor == 1;
+
+ static_assert(k_factor <= 4 && k_factor > 0,
+ "innerkernel maximum k_factor supported is 4");
+
+ if (k_factor > 0) innerkernel_1uk<0, max_b_unroll, a_unroll, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+ if (k_factor > 1) innerkernel_1uk<1, max_b_unroll, a_unroll, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+ if (k_factor > 2) innerkernel_1uk<2, max_b_unroll, a_unroll, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+ if (k_factor > 3) innerkernel_1uk<3, max_b_unroll, a_unroll, b_unroll, ktail, fetch_x, c_fetch>(aa, ao, bo, co2, fetchA_idx, fetchB_idx);
+
+ // Advance A/B pointers after uk-loop.
+ ao += a_unroll * k_factor;
+ bo += b_unroll * k_factor;
+ }
+
+
+ template <int a_unroll, int b_unroll, int max_b_unroll>
+ EIGEN_ALWAYS_INLINE void kloop(const Scalar *&aa, const Scalar *&ao, const Scalar *&bo, Scalar *&co1, Scalar *&co2)
+ {
+ const int um_vecs = div_up(a_unroll, nelems_in_cache_line);
+#ifndef EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_A_REGS
+ a_loads<0, 2, 0, um_vecs, a_unroll>(ao);
+#else
+ a_loads<0, 1, 0, um_vecs, a_unroll>(ao);
+#endif
+
+ b_load(zmm[b_regs[0]], bo - b_shift + 0);
+#ifndef EIGEN_ARCH_AVX512_GEMM_KERNEL_USE_LESS_B_REGS
+ b_load(zmm[b_regs[1]], bo - b_shift + 1);
+#endif
+
+#ifndef SECOND_FETCH
+ prefetch_cs<0, max_b_unroll, 0, um_vecs, a_unroll, b_unroll>(co1, co2);
+#endif // SECOND_FETCH
+
+ // Unrolling k-loop by a factor of 4.
+ const int max_k_factor = 4;
+ int64_t loop_count = k / max_k_factor;
+
+ if (loop_count > 0) {
+#ifdef SECOND_FETCH
+ loop_count -= SECOND_FETCH;
+#endif
+ while (loop_count > 0) {
+ innerkernel<a_unroll, b_unroll, max_k_factor, max_b_unroll, max_k_factor, 0>(aa, ao, bo, co2);
+ loop_count--;
+ }
+#ifdef SECOND_FETCH
+ co2 = co1 + nelems_in_cache_line - 1;
+
+ loop_count += b_unroll;
+ while (loop_count > 0) {
+ innerkernel<a_unroll, b_unroll, max_k_factor, max_b_unroll, max_k_factor, 1>(aa, ao, bo, co2);
+ loop_count--;
+ }
+
+ loop_count += SECOND_FETCH - b_unroll;
+ while (loop_count > 0) {
+ innerkernel<a_unroll, b_unroll, max_k_factor, max_b_unroll, max_k_factor, 0>(aa, ao, bo, co2);
+ loop_count--;
+ }
+#endif
+ }
+
+ // k-loop remainder handling.
+ loop_count = k % max_k_factor;
+ while (loop_count > 0) {
+ innerkernel<a_unroll, b_unroll, 1, max_b_unroll, max_k_factor, 0>(aa, ao, bo, co2);
+ loop_count--;
+ }
+
+ // Update C matrix.
+ c_update<1, max_b_unroll, 1, a_unroll, b_unroll, 0>(co1, co2);
+ }
+
+ template <int a_unroll, int b_unroll, int max_b_unroll>
+ EIGEN_ALWAYS_INLINE void nloop(const Scalar *&aa, const Scalar *&ao, const Scalar *&bo, Scalar *&co1, Scalar *&co2)
+ {
+ // Set A matrix pointer.
+ ao = a + a_off * a_unroll;
+
+ // Set B matrix pointer if needed.
+ bo += b_unroll * b_off;
+
+ kloop<a_unroll, b_unroll, max_b_unroll>(aa, ao, bo, co1, co2);
+
+ // Advance B matrix pointer if needed.
+ bo += b_unroll * (b_stride - k - b_off);
+
+ // Advance prefetch A pointer.
+ aa += 16;
+ }
+
+ template <int a_unroll, int max_a_unroll, int max_b_unroll>
+ EIGEN_ALWAYS_INLINE void mloop(const Scalar *&ao, const Scalar *&bo, Scalar *&co1, Scalar *&co2)
+ {
+ // Set prefetch A pointers.
+ const Scalar *aa = a + a_unroll * a_stride;
+
+ // Set C matrix pointers.
+ co1 = c;
+ if (a_unroll >= max_a_unroll) co2 = c + 2 * ldc;
+ c += a_unroll;
+
+ // Set B matrix pointer.
+ bo = b;
+
+ // Main n-loop.
+ for (int64_t i = n / max_b_unroll; i > 0; i--)
+ nloop<a_unroll, max_b_unroll, max_b_unroll>(aa, ao, bo, co1, co2);
+
+ // n-remainders.
+ if (n & 4 && max_b_unroll > 4) nloop<a_unroll, 4, max_b_unroll>(aa, ao, bo, co1, co2);
+#if 0
+ if (n & 2 && max_b_unroll > 2) nloop<a_unroll, 2, max_b_unroll>(aa, ao, bo, co1, co2);
+ if (n & 1 && max_b_unroll > 1) nloop<a_unroll, 1, max_b_unroll>(aa, ao, bo, co1, co2);
+#else
+ // Copy kernels don't support tails of n = 2 for single/double precision.
+ // Loop over ones.
+ int n_rem = 2 * ((n & 2) != 0) + 1 * ((n & 1) != 0);
+ while (n_rem > 0) {nloop<a_unroll, 1, max_b_unroll>(aa, ao, bo, co1, co2); n_rem--;}
+#endif
+
+ // Advance A matrix pointer.
+ a = ao + a_unroll * (a_stride - k - a_off);
+ }
+
+ // Compute kernel unrolling C matrix by max_a_unroll x max_b_unroll.
+ template <int max_a_unroll, int max_b_unroll>
+ EIGEN_ALWAYS_INLINE void compute_kern()
+ {
+ a -= -a_shift;
+ b -= -b_shift;
+
+ const Scalar *ao = nullptr;
+ const Scalar *bo = nullptr;
+ Scalar *co1 = nullptr;
+ Scalar *co2 = nullptr;
+
+ // Main m-loop.
+ for (; m >= max_a_unroll; m -= max_a_unroll)
+ mloop<max_a_unroll, max_a_unroll, max_b_unroll>(ao, bo, co1, co2);
+
+ // m-remainders.
+ if (m & 32 && max_a_unroll > 32) mloop<32, max_a_unroll, max_b_unroll>(ao, bo, co1, co2);
+ if (m & 16 && max_a_unroll > 16) mloop<16, max_a_unroll, max_b_unroll>(ao, bo, co1, co2);
+ if (m & 8 && max_a_unroll > 8) mloop< 8, max_a_unroll, max_b_unroll>(ao, bo, co1, co2);
+ if (m & 4 && max_a_unroll > 4) mloop< 4, max_a_unroll, max_b_unroll>(ao, bo, co1, co2);
+ if (m & 2 && max_a_unroll > 2 && is_f64) mloop< 2, max_a_unroll, max_b_unroll>(ao, bo, co1, co2);
+ if (m & 1 && max_a_unroll > 1 && is_f64) mloop< 1, max_a_unroll, max_b_unroll>(ao, bo, co1, co2);
+
+ // Copy kernels don't support tails of m = 2 for single precision.
+ // Loop over ones.
+ if (is_f32) {
+ int m_rem = 2 * ((m & 2) != 0) + 1 * ((m & 1) != 0);
+ while (m_rem > 0) {mloop< 1, max_a_unroll, max_b_unroll>(ao, bo, co1, co2); m_rem--;}
+ }
+ }
+};
+
+// Compute kernel with max unroll support of:
+// Single precision:
+// max_a_unroll: 48, 32, 16, 8, 4, 2, 1
+// max_b_unroll: 8, 4, 2, 1
+// Double precision:
+// max_a_unroll: 24, 16, 8, 4, 2, 1
+// max_b_unroll: 8, 4, 2, 1
+template <typename Scalar, int max_a_unroll, int max_b_unroll, bool is_alpha1, bool is_beta0>
+EIGEN_DONT_INLINE void gemm_kern_avx512(int64_t *p_m, int64_t *p_n, int64_t *p_k,
+ Scalar *alpha, const Scalar *a, const Scalar *b, Scalar *c,
+ int64_t ldc, int64_t a_stride = -1, int64_t b_stride = -1,
+ int64_t a_off = 0, int64_t b_off = 0)
+{
+ if (a_stride == -1) a_stride = *p_k;
+ if (b_stride == -1) b_stride = *p_k;
+
+ gemm_class<Scalar> g(*p_m, *p_n, *p_k, ldc, alpha, a, b, c,
+ is_alpha1, is_beta0, a_stride, b_stride, a_off, b_off);
+ g.template compute_kern<max_a_unroll, max_b_unroll>();
+}
+
+template <typename a_t, typename b_t, typename c_t>
+bool gemm_kernel(int64_t m, int64_t n, int64_t k, c_t alpha,
+ const a_t *a, const b_t *b, c_t *c, int64_t ldc,
+ int64_t a_stride = -1, int64_t b_stride = -1,
+ int64_t a_off = 0, int64_t b_off = 0)
+{
+ EIGEN_UNUSED_VARIABLE(m);
+ EIGEN_UNUSED_VARIABLE(n);
+ EIGEN_UNUSED_VARIABLE(k);
+ EIGEN_UNUSED_VARIABLE(alpha);
+ EIGEN_UNUSED_VARIABLE(a);
+ EIGEN_UNUSED_VARIABLE(b);
+ EIGEN_UNUSED_VARIABLE(c);
+ EIGEN_UNUSED_VARIABLE(ldc);
+ EIGEN_UNUSED_VARIABLE(a_stride);
+ EIGEN_UNUSED_VARIABLE(b_stride);
+ EIGEN_UNUSED_VARIABLE(a_off);
+ EIGEN_UNUSED_VARIABLE(b_off);
+ return false;
+}
+
+template <>
+bool gemm_kernel(int64_t m, int64_t n, int64_t k, float alpha,
+ const float *a, const float *b, float *c, int64_t ldc,
+ int64_t a_stride, int64_t b_stride,
+ int64_t a_off, int64_t b_off)
+{
+ if (alpha == 1.f)
+ gemm_kern_avx512<float, 48, 8, true, false>(&m, &n, &k, &alpha, a, b, c,
+ ldc, a_stride, b_stride, a_off, b_off);
+ else
+ gemm_kern_avx512<float, 48, 8, false, false>(&m, &n, &k, &alpha, a, b, c,
+ ldc, a_stride, b_stride, a_off, b_off);
+
+ return true;
+}
+
+template <>
+bool gemm_kernel(int64_t m, int64_t n, int64_t k, double alpha,
+ const double *a, const double *b, double *c, int64_t ldc,
+ int64_t a_stride, int64_t b_stride,
+ int64_t a_off, int64_t b_off)
+{
+ if (alpha == 1.)
+ gemm_kern_avx512<double, 24, 8, true, false>(&m, &n, &k, &alpha, a, b, c,
+ ldc, a_stride, b_stride, a_off, b_off);
+ else
+ gemm_kern_avx512<double, 24, 8, false, false>(&m, &n, &k, &alpha, a, b, c,
+ ldc, a_stride, b_stride, a_off, b_off);
+
+ return true;
+}
+
+template<typename Scalar, typename Index, typename DataMapper, int nr, int StorageOrder, bool Conjugate, bool PanelMode>
+struct gemm_pack_rhs;
+
+template<typename Scalar, typename Index, typename DataMapper, bool Conjugate, bool PanelMode>
+struct gemm_pack_rhs<Scalar, Index, DataMapper, 8, ColMajor, Conjugate, PanelMode>
+{
+ typedef typename packet_traits<Scalar>::type Packet;
+ typedef typename DataMapper::LinearMapper LinearMapper;
+ enum { PacketSize = packet_traits<Scalar>::size };
+ EIGEN_DONT_INLINE void operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride=0, Index offset=0);
+};
+
+template<typename Scalar, typename Index, typename DataMapper, bool Conjugate, bool PanelMode>
+EIGEN_DONT_INLINE void gemm_pack_rhs<Scalar, Index, DataMapper, 8, ColMajor, Conjugate, PanelMode>
+ ::operator()(Scalar* blockB, const DataMapper& rhs, Index depth, Index cols, Index stride, Index offset)
+{
+ constexpr int nr = 8;
+ EIGEN_ASM_COMMENT("EIGEN PRODUCT PACK RHS COLMAJOR");
+ EIGEN_UNUSED_VARIABLE(stride);
+ EIGEN_UNUSED_VARIABLE(offset);
+ eigen_assert(((!PanelMode) && stride==0 && offset==0) || (PanelMode && stride>=depth && offset<=stride));
+ conj_if<NumTraits<Scalar>::IsComplex && Conjugate> cj;
+ Index packet_cols8 = nr>=8 ? (cols/8) * 8 : 0;
+ Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
+ Index count = 0;
+ const Index peeled_k = (depth/PacketSize)*PacketSize;
+ if(nr>=8)
+ {
+ for(Index j2=0; j2<packet_cols8; j2+=8)
+ {
+ // skip what we have before
+ if(PanelMode) count += 8 * offset;
+ const LinearMapper dm0 = rhs.getLinearMapper(0, j2+0);
+ const LinearMapper dm1 = rhs.getLinearMapper(0, j2+1);
+ const LinearMapper dm2 = rhs.getLinearMapper(0, j2+2);
+ const LinearMapper dm3 = rhs.getLinearMapper(0, j2+3);
+ const LinearMapper dm4 = rhs.getLinearMapper(0, j2+4);
+ const LinearMapper dm5 = rhs.getLinearMapper(0, j2+5);
+ const LinearMapper dm6 = rhs.getLinearMapper(0, j2+6);
+ const LinearMapper dm7 = rhs.getLinearMapper(0, j2+7);
+ Index k=0;
+ if((PacketSize%8)==0) // TODO enable vectorized transposition for PacketSize==4
+ {
+ for(; k<peeled_k; k+=PacketSize) {
+ PacketBlock<Packet,(PacketSize%8)==0?8:PacketSize> kernel;
+
+ kernel.packet[0] = dm0.template loadPacket<Packet>(k);
+ kernel.packet[1] = dm1.template loadPacket<Packet>(k);
+ kernel.packet[2] = dm2.template loadPacket<Packet>(k);
+ kernel.packet[3] = dm3.template loadPacket<Packet>(k);
+ kernel.packet[4] = dm4.template loadPacket<Packet>(k);
+ kernel.packet[5] = dm5.template loadPacket<Packet>(k);
+ kernel.packet[6] = dm6.template loadPacket<Packet>(k);
+ kernel.packet[7] = dm7.template loadPacket<Packet>(k);
+
+ ptranspose(kernel);
+
+ pstoreu(blockB+count+0*PacketSize, cj.pconj(kernel.packet[0]));
+ pstoreu(blockB+count+1*PacketSize, cj.pconj(kernel.packet[1%PacketSize]));
+ pstoreu(blockB+count+2*PacketSize, cj.pconj(kernel.packet[2%PacketSize]));
+ pstoreu(blockB+count+3*PacketSize, cj.pconj(kernel.packet[3%PacketSize]));
+ pstoreu(blockB+count+4*PacketSize, cj.pconj(kernel.packet[4%PacketSize]));
+ pstoreu(blockB+count+5*PacketSize, cj.pconj(kernel.packet[5%PacketSize]));
+ pstoreu(blockB+count+6*PacketSize, cj.pconj(kernel.packet[6%PacketSize]));
+ pstoreu(blockB+count+7*PacketSize, cj.pconj(kernel.packet[7%PacketSize]));
+ count+=8*PacketSize;
+ }
+ }
+ for(; k<depth; k++)
+ {
+ blockB[count+0] = cj(dm0(k));
+ blockB[count+1] = cj(dm1(k));
+ blockB[count+2] = cj(dm2(k));
+ blockB[count+3] = cj(dm3(k));
+ blockB[count+4] = cj(dm4(k));
+ blockB[count+5] = cj(dm5(k));
+ blockB[count+6] = cj(dm6(k));
+ blockB[count+7] = cj(dm7(k));
+ count += 8;
+ }
+ // skip what we have after
+ if(PanelMode) count += 8 * (stride-offset-depth);
+ }
+ }
+
+ if(nr>=4)
+ {
+ for(Index j2=packet_cols8; j2<packet_cols4; j2+=4)
+ {
+ // skip what we have before
+ if(PanelMode) count += 4 * offset;
+ const LinearMapper dm0 = rhs.getLinearMapper(0, j2 + 0);
+ const LinearMapper dm1 = rhs.getLinearMapper(0, j2 + 1);
+ const LinearMapper dm2 = rhs.getLinearMapper(0, j2 + 2);
+ const LinearMapper dm3 = rhs.getLinearMapper(0, j2 + 3);
+
+ Index k=0;
+ if((PacketSize%4)==0) // TODO enable vectorized transposition for PacketSize==2 ??
+ {
+ for(; k<peeled_k; k+=PacketSize) {
+ PacketBlock<Packet,(PacketSize%4)==0?4:PacketSize> kernel;
+ kernel.packet[0 ] = dm0.template loadPacket<Packet>(k);
+ kernel.packet[1%PacketSize] = dm1.template loadPacket<Packet>(k);
+ kernel.packet[2%PacketSize] = dm2.template loadPacket<Packet>(k);
+ kernel.packet[3%PacketSize] = dm3.template loadPacket<Packet>(k);
+ ptranspose(kernel);
+ pstoreu(blockB+count+0*PacketSize, cj.pconj(kernel.packet[0]));
+ pstoreu(blockB+count+1*PacketSize, cj.pconj(kernel.packet[1%PacketSize]));
+ pstoreu(blockB+count+2*PacketSize, cj.pconj(kernel.packet[2%PacketSize]));
+ pstoreu(blockB+count+3*PacketSize, cj.pconj(kernel.packet[3%PacketSize]));
+ count+=4*PacketSize;
+ }
+ }
+ for(; k<depth; k++)
+ {
+ blockB[count+0] = cj(dm0(k));
+ blockB[count+1] = cj(dm1(k));
+ blockB[count+2] = cj(dm2(k));
+ blockB[count+3] = cj(dm3(k));
+ count += 4;
+ }
+ // skip what we have after
+ if(PanelMode) count += 4 * (stride-offset-depth);
+ }
+ }
+
+ // copy the remaining columns one at a time (nr==1)
+ for(Index j2=packet_cols4; j2<cols; ++j2)
+ {
+ if(PanelMode) count += offset;
+ const LinearMapper dm0 = rhs.getLinearMapper(0, j2);
+ for(Index k=0; k<depth; k++)
+ {
+ blockB[count] = cj(dm0(k));
+ count += 1;
+ }
+ if(PanelMode) count += (stride-offset-depth);
+ }
+}
+
+} // namespace Eigen
+} // namespace internal
+
+#endif // GEMM_KERNEL_H
diff --git a/Eigen/src/Core/arch/AVX512/PacketMath.h b/Eigen/src/Core/arch/AVX512/PacketMath.h
index 337001b..466418a 100644
--- a/Eigen/src/Core/arch/AVX512/PacketMath.h
+++ b/Eigen/src/Core/arch/AVX512/PacketMath.h
@@ -1432,6 +1432,7 @@
EIGEN_INSERT_8f_INTO_16f(OUTPUT[INDEX], INPUT[2 * INDEX], \
INPUT[2 * INDEX + STRIDE]);
+template<bool for_trsm = false>
EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet16f, 8>& kernel) {
__m512 T0 = _mm512_unpacklo_ps(kernel.packet[0],kernel.packet[1]);
__m512 T1 = _mm512_unpackhi_ps(kernel.packet[0],kernel.packet[1]);
@@ -1450,28 +1451,49 @@
kernel.packet[5] = _mm512_castpd_ps(_mm512_unpackhi_pd(_mm512_castps_pd(T4),_mm512_castps_pd(T6)));
kernel.packet[6] = _mm512_castpd_ps(_mm512_unpacklo_pd(_mm512_castps_pd(T5),_mm512_castps_pd(T7)));
kernel.packet[7] = _mm512_castpd_ps(_mm512_unpackhi_pd(_mm512_castps_pd(T5),_mm512_castps_pd(T7)));
-
- T0 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[4]), 0x4E));
- T0 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[0], T0);
- T4 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[0]), 0x4E));
- T4 = _mm512_mask_blend_ps(0xF0F0, T4, kernel.packet[4]);
- T1 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[5]), 0x4E));
- T1 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[1], T1);
- T5 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[1]), 0x4E));
- T5 = _mm512_mask_blend_ps(0xF0F0, T5, kernel.packet[5]);
- T2 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[6]), 0x4E));
- T2 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[2], T2);
- T6 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[2]), 0x4E));
- T6 = _mm512_mask_blend_ps(0xF0F0, T6, kernel.packet[6]);
- T3 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[7]), 0x4E));
- T3 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[3], T3);
- T7 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[3]), 0x4E));
- T7 = _mm512_mask_blend_ps(0xF0F0, T7, kernel.packet[7]);
- kernel.packet[0] = T0; kernel.packet[1] = T1;
- kernel.packet[2] = T2; kernel.packet[3] = T3;
- kernel.packet[4] = T4; kernel.packet[5] = T5;
- kernel.packet[6] = T6; kernel.packet[7] = T7;
+ // Transpose for gemm is slightly different than trsm.
+ if (!for_trsm) {
+ T0 = _mm512_shuffle_f32x4(kernel.packet[0], kernel.packet[4], 0x44);
+ T1 = _mm512_shuffle_f32x4(kernel.packet[0], kernel.packet[4], 0xee);
+ T2 = _mm512_shuffle_f32x4(kernel.packet[1], kernel.packet[5], 0x44);
+ T3 = _mm512_shuffle_f32x4(kernel.packet[1], kernel.packet[5], 0xee);
+ T4 = _mm512_shuffle_f32x4(kernel.packet[2], kernel.packet[6], 0x44);
+ T5 = _mm512_shuffle_f32x4(kernel.packet[2], kernel.packet[6], 0xee);
+ T6 = _mm512_shuffle_f32x4(kernel.packet[3], kernel.packet[7], 0x44);
+ T7 = _mm512_shuffle_f32x4(kernel.packet[3], kernel.packet[7], 0xee);
+
+ kernel.packet[0] = _mm512_shuffle_f32x4(T0, T2, 0x88);
+ kernel.packet[2] = _mm512_shuffle_f32x4(T0, T2, 0xdd);
+ kernel.packet[1] = _mm512_shuffle_f32x4(T4, T6, 0x88);
+ kernel.packet[3] = _mm512_shuffle_f32x4(T4, T6, 0xdd);
+ kernel.packet[4] = _mm512_shuffle_f32x4(T1, T3, 0x88);
+ kernel.packet[6] = _mm512_shuffle_f32x4(T1, T3, 0xdd);
+ kernel.packet[5] = _mm512_shuffle_f32x4(T5, T7, 0x88);
+ kernel.packet[7] = _mm512_shuffle_f32x4(T5, T7, 0xdd);
+ } else {
+ T0 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[4]), 0x4E));
+ T0 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[0], T0);
+ T4 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[0]), 0x4E));
+ T4 = _mm512_mask_blend_ps(0xF0F0, T4, kernel.packet[4]);
+ T1 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[5]), 0x4E));
+ T1 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[1], T1);
+ T5 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[1]), 0x4E));
+ T5 = _mm512_mask_blend_ps(0xF0F0, T5, kernel.packet[5]);
+ T2 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[6]), 0x4E));
+ T2 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[2], T2);
+ T6 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[2]), 0x4E));
+ T6 = _mm512_mask_blend_ps(0xF0F0, T6, kernel.packet[6]);
+ T3 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[7]), 0x4E));
+ T3 = _mm512_mask_blend_ps(0xF0F0, kernel.packet[3], T3);
+ T7 = _mm512_castpd_ps(_mm512_permutex_pd(_mm512_castps_pd(kernel.packet[3]), 0x4E));
+ T7 = _mm512_mask_blend_ps(0xF0F0, T7, kernel.packet[7]);
+
+ kernel.packet[0] = T0; kernel.packet[1] = T1;
+ kernel.packet[2] = T2; kernel.packet[3] = T3;
+ kernel.packet[4] = T4; kernel.packet[5] = T5;
+ kernel.packet[6] = T6; kernel.packet[7] = T7;
+ }
}
EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet16f, 4>& kernel) {
@@ -1549,7 +1571,9 @@
PACK_OUTPUT_D(kernel.packet, tmp.packet, 3, 1);
}
+template<bool for_trsm = false>
EIGEN_DEVICE_FUNC inline void ptranspose(PacketBlock<Packet8d, 8>& kernel) {
+ // Transpose for trsm is the same as for gemm.
__m512d T0 = _mm512_unpacklo_pd(kernel.packet[0],kernel.packet[1]);
__m512d T1 = _mm512_unpackhi_pd(kernel.packet[0],kernel.packet[1]);
__m512d T2 = _mm512_unpacklo_pd(kernel.packet[2],kernel.packet[3]);
diff --git a/Eigen/src/Core/arch/AVX512/TrsmUnrolls.inc b/Eigen/src/Core/arch/AVX512/TrsmUnrolls.inc
index 22cb1c9..9fd7de9 100644
--- a/Eigen/src/Core/arch/AVX512/TrsmUnrolls.inc
+++ b/Eigen/src/Core/arch/AVX512/TrsmUnrolls.inc
@@ -198,7 +198,7 @@
r.packet[5] = zmm.packet[packetIndexOffset + zmmStride*5];
r.packet[6] = zmm.packet[packetIndexOffset + zmmStride*6];
r.packet[7] = zmm.packet[packetIndexOffset + zmmStride*7];
- ptranspose(r);
+ ptranspose<true>(r);
zmm.packet[packetIndexOffset + zmmStride*0] = r.packet[0];
zmm.packet[packetIndexOffset + zmmStride*1] = r.packet[1];
zmm.packet[packetIndexOffset + zmmStride*2] = r.packet[2];
diff --git a/Eigen/src/Core/arch/AVX512/TypeCasting.h b/Eigen/src/Core/arch/AVX512/TypeCasting.h
index 8baced1..d28cca2 100644
--- a/Eigen/src/Core/arch/AVX512/TypeCasting.h
+++ b/Eigen/src/Core/arch/AVX512/TypeCasting.h
@@ -44,6 +44,34 @@
return _mm512_castps512_ps256(a);
}
+template<> EIGEN_STRONG_INLINE Packet4f preinterpret<Packet4f, Packet16f>(const Packet16f& a) {
+ return _mm512_castps512_ps128(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4d preinterpret<Packet4d, Packet8d>(const Packet8d& a) {
+ return _mm512_castpd512_pd256(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet2d preinterpret<Packet2d, Packet8d>(const Packet8d& a) {
+ return _mm512_castpd512_pd128(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet16f preinterpret<Packet16f, Packet8f>(const Packet8f& a) {
+ return _mm512_castps256_ps512(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet16f preinterpret<Packet16f, Packet4f>(const Packet4f& a) {
+ return _mm512_castps128_ps512(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8d preinterpret<Packet8d, Packet4d>(const Packet4d& a) {
+ return _mm512_castpd256_pd512(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet8d preinterpret<Packet8d, Packet2d>(const Packet2d& a) {
+ return _mm512_castpd128_pd512(a);
+}
+
template<> EIGEN_STRONG_INLINE Packet16f preinterpret<Packet16f, Packet16f>(const Packet16f& a) {
return a;
}
diff --git a/Eigen/src/Core/arch/NEON/GeneralBlockPanelKernel.h b/Eigen/src/Core/arch/NEON/GeneralBlockPanelKernel.h
index 6cd6edd..d64b1a0 100644
--- a/Eigen/src/Core/arch/NEON/GeneralBlockPanelKernel.h
+++ b/Eigen/src/Core/arch/NEON/GeneralBlockPanelKernel.h
@@ -8,9 +8,9 @@
// Clang seems to excessively spill registers in the GEBP kernel on 32-bit arm.
// Here we specialize gebp_traits to eliminate these register spills.
// See #2138.
-template<>
-struct gebp_traits <float,float,false,false,Architecture::NEON,GEBPPacketFull>
- : gebp_traits<float,float,false,false,Architecture::Generic,GEBPPacketFull>
+template<bool UnitResIncr>
+struct gebp_traits <float,float,UnitResIncr,false,false,Architecture::NEON,GEBPPacketFull>
+ : gebp_traits<float,float,UnitResIncr,false,false,Architecture::Generic,GEBPPacketFull>
{
EIGEN_STRONG_INLINE void acc(const AccPacket& c, const ResPacket& alpha, ResPacket& r) const
{
@@ -43,9 +43,9 @@
#if EIGEN_ARCH_ARM64
-template<>
-struct gebp_traits <float,float,false,false,Architecture::NEON,GEBPPacketFull>
- : gebp_traits<float,float,false,false,Architecture::Generic,GEBPPacketFull>
+template<bool UnitResIncr>
+struct gebp_traits <float,float,UnitResIncr,false,false,Architecture::NEON,GEBPPacketFull>
+ : gebp_traits<float,float,UnitResIncr,false,false,Architecture::Generic,GEBPPacketFull>
{
typedef float RhsPacket;
typedef float32x4_t RhsPacketx4;
@@ -108,9 +108,9 @@
};
-template<>
-struct gebp_traits <double,double,false,false,Architecture::NEON>
- : gebp_traits<double,double,false,false,Architecture::Generic>
+template<bool UnitResIncr>
+struct gebp_traits <double,double,UnitResIncr,false,false,Architecture::NEON>
+ : gebp_traits<double,double,UnitResIncr,false,false,Architecture::Generic>
{
typedef double RhsPacket;
diff --git a/Eigen/src/Core/arch/SSE/PacketMath.h b/Eigen/src/Core/arch/SSE/PacketMath.h
index 35490a6..e896040 100755
--- a/Eigen/src/Core/arch/SSE/PacketMath.h
+++ b/Eigen/src/Core/arch/SSE/PacketMath.h
@@ -285,6 +285,10 @@
template<> EIGEN_STRONG_INLINE Packet16b padd<Packet16b>(const Packet16b& a, const Packet16b& b) { return _mm_or_si128(a,b); }
+template<typename Packet> EIGEN_STRONG_INLINE Packet padds(const Packet& a, const Packet& b);
+template<> EIGEN_STRONG_INLINE Packet4f padds<Packet4f>(const Packet4f& a, const Packet4f& b) { return _mm_add_ss(a,b); }
+template<> EIGEN_STRONG_INLINE Packet2d padds<Packet2d>(const Packet2d& a, const Packet2d& b) { return _mm_add_sd(a,b); }
+
template<> EIGEN_STRONG_INLINE Packet4f psub<Packet4f>(const Packet4f& a, const Packet4f& b) { return _mm_sub_ps(a,b); }
template<> EIGEN_STRONG_INLINE Packet2d psub<Packet2d>(const Packet2d& a, const Packet2d& b) { return _mm_sub_pd(a,b); }
template<> EIGEN_STRONG_INLINE Packet4i psub<Packet4i>(const Packet4i& a, const Packet4i& b) { return _mm_sub_epi32(a,b); }
@@ -370,6 +374,10 @@
template<> EIGEN_STRONG_INLINE Packet2d pnmadd(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return _mm_fnmadd_pd(a,b,c); }
template<> EIGEN_STRONG_INLINE Packet4f pnmsub(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return _mm_fnmsub_ps(a,b,c); }
template<> EIGEN_STRONG_INLINE Packet2d pnmsub(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return _mm_fnmsub_pd(a,b,c); }
+
+template<typename Packet> EIGEN_STRONG_INLINE Packet pmadds(const Packet& a, const Packet& b, const Packet& c);
+template<> EIGEN_STRONG_INLINE Packet4f pmadds<Packet4f>(const Packet4f& a, const Packet4f& b, const Packet4f& c) { return _mm_fmadd_ss(a,b,c); }
+template<> EIGEN_STRONG_INLINE Packet2d pmadds<Packet2d>(const Packet2d& a, const Packet2d& b, const Packet2d& c) { return _mm_fmadd_sd(a,b,c); }
#endif
#ifdef EIGEN_VECTORIZE_SSE4_1
@@ -746,6 +754,15 @@
return _mm_loadu_si128(reinterpret_cast<const __m128i*>(from));
}
+// Load lower part of packet zero extending.
+template<typename Packet> EIGEN_STRONG_INLINE Packet ploadl(const typename unpacket_traits<Packet>::type* from);
+template<> EIGEN_STRONG_INLINE Packet4f ploadl<Packet4f>(const float* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm_castpd_ps(_mm_load_sd(reinterpret_cast<const double*>(from))); }
+template<> EIGEN_STRONG_INLINE Packet2d ploadl<Packet2d>(const double* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm_load_sd(from); }
+
+// Load scalar
+template<typename Packet> EIGEN_STRONG_INLINE Packet ploads(const typename unpacket_traits<Packet>::type* from);
+template<> EIGEN_STRONG_INLINE Packet4f ploads<Packet4f>(const float* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm_load_ss(from); }
+template<> EIGEN_STRONG_INLINE Packet2d ploads<Packet2d>(const double* from) { EIGEN_DEBUG_UNALIGNED_LOAD return _mm_load_sd(from); }
template<> EIGEN_STRONG_INLINE Packet4f ploaddup<Packet4f>(const float* from)
{
@@ -787,6 +804,14 @@
template<> EIGEN_STRONG_INLINE void pstoreu<int>(int* to, const Packet4i& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_storeu_si128(reinterpret_cast<__m128i*>(to), from); }
template<> EIGEN_STRONG_INLINE void pstoreu<bool>(bool* to, const Packet16b& from) { EIGEN_DEBUG_ALIGNED_STORE _mm_storeu_si128(reinterpret_cast<__m128i*>(to), from); }
+template<typename Scalar, typename Packet> EIGEN_STRONG_INLINE void pstorel(Scalar* to, const Packet& from);
+template<> EIGEN_STRONG_INLINE void pstorel(float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_storel_pi(reinterpret_cast<__m64*>(to), from); }
+template<> EIGEN_STRONG_INLINE void pstorel(double* to, const Packet2d& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_storel_pd(to, from); }
+
+template<typename Scalar, typename Packet> EIGEN_STRONG_INLINE void pstores(Scalar* to, const Packet& from);
+template<> EIGEN_STRONG_INLINE void pstores(float* to, const Packet4f& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_store_ss(to, from); }
+template<> EIGEN_STRONG_INLINE void pstores(double* to, const Packet2d& from) { EIGEN_DEBUG_UNALIGNED_STORE _mm_store_sd(to, from); }
+
template<> EIGEN_DEVICE_FUNC inline Packet4f pgather<float, Packet4f>(const float* from, Index stride)
{
return _mm_set_ps(from[3*stride], from[2*stride], from[1*stride], from[0*stride]);
diff --git a/Eigen/src/Core/arch/SSE/TypeCasting.h b/Eigen/src/Core/arch/SSE/TypeCasting.h
index c21d1ac..a6346ea 100644
--- a/Eigen/src/Core/arch/SSE/TypeCasting.h
+++ b/Eigen/src/Core/arch/SSE/TypeCasting.h
@@ -71,6 +71,14 @@
return _mm_cvtps_pd(a);
}
+template<> EIGEN_STRONG_INLINE Packet2d preinterpret<Packet2d, Packet4f>(const Packet4f& a) {
+ return _mm_castps_pd(a);
+}
+
+template<> EIGEN_STRONG_INLINE Packet4f preinterpret<Packet4f, Packet2d>(const Packet2d& a) {
+ return _mm_castpd_ps(a);
+}
+
template<> EIGEN_STRONG_INLINE Packet4i preinterpret<Packet4i,Packet4f>(const Packet4f& a) {
return _mm_castps_si128(a);
}
diff --git a/Eigen/src/Core/products/GeneralBlockPanelKernel.h b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
index b1a1277..2502cd9 100644
--- a/Eigen/src/Core/products/GeneralBlockPanelKernel.h
+++ b/Eigen/src/Core/products/GeneralBlockPanelKernel.h
@@ -2,6 +2,7 @@
// for linear algebra.
//
// Copyright (C) 2008-2009 Gael Guennebaud <gael.guennebaud@inria.fr>
+// Modifications Copyright (C) 2022 Intel Corporation
//
// This Source Code Form is subject to the terms of the Mozilla
// Public License v. 2.0. If a copy of the MPL was not distributed
@@ -23,7 +24,7 @@
GEBPPacketQuarter
};
-template<typename LhsScalar_, typename RhsScalar_, bool ConjLhs_=false, bool ConjRhs_=false, int Arch=Architecture::Target, int PacketSize_=GEBPPacketFull>
+template<typename LhsScalar_, typename RhsScalar_, bool UnitResIncr=false, bool ConjLhs_=false, bool ConjRhs_=false, int Arch=Architecture::Target, int PacketSize_=GEBPPacketFull>
class gebp_traits;
@@ -125,7 +126,7 @@
template<typename LhsScalar, typename RhsScalar, int KcFactor, typename Index>
void evaluateProductBlockingSizesHeuristic(Index& k, Index& m, Index& n, Index num_threads = 1)
{
- typedef gebp_traits<LhsScalar,RhsScalar> Traits;
+ typedef gebp_traits<LhsScalar,RhsScalar, true> Traits;
// Explanations:
// Let's recall that the product algorithms form mc x kc vertical panels A' on the lhs and
@@ -416,7 +417,7 @@
* cplx*real : unpack rhs to constant packets, ...
* real*cplx : load lhs as (a0,a0,a1,a1), and mul as usual
*/
-template<typename LhsScalar_, typename RhsScalar_, bool ConjLhs_, bool ConjRhs_, int Arch, int PacketSize_>
+template<typename LhsScalar_, typename RhsScalar_, bool UnitResIncr_, bool ConjLhs_, bool ConjRhs_, int Arch, int PacketSize_>
class gebp_traits
{
public:
@@ -429,6 +430,7 @@
PACKET_DECL_COND_POSTFIX(_, Res, PacketSize_);
enum {
+ UnitResIncr = UnitResIncr_,
ConjLhs = ConjLhs_,
ConjRhs = ConjRhs_,
Vectorizable = unpacket_traits<LhsPacket_>::vectorizable && unpacket_traits<RhsPacket_>::vectorizable,
@@ -437,9 +439,17 @@
ResPacketSize = Vectorizable ? unpacket_traits<ResPacket_>::size : 1,
NumberOfRegisters = EIGEN_ARCH_DEFAULT_NUMBER_OF_REGISTERS,
+ IsReal = std::is_same<LhsScalar, RhsScalar>::value
+ && (std::is_same<LhsScalar, float>::value
+ || std::is_same<LhsScalar, double>::value),
// register block size along the N direction must be 1 or 4
+#if defined(EIGEN_VECTORIZE_AVX512)
+ // AVX512 support nr = 8 for unit inner strides for result matrix.
+ nr = IsReal && Vectorizable && UnitResIncr ? 8 : 4,
+#else
nr = 4,
+#endif
// register block size along the M direction (currently, this one cannot be modified)
default_mr = (plain_enum_min(16, NumberOfRegisters)/2/nr)*LhsPacketSize,
@@ -545,8 +555,9 @@
};
-template<typename RealScalar, bool ConjLhs_, int Arch, int PacketSize_>
-class gebp_traits<std::complex<RealScalar>, RealScalar, ConjLhs_, false, Arch, PacketSize_>
+
+template<typename RealScalar, bool UnitResIncr_, bool ConjLhs_, int Arch, int PacketSize_>
+class gebp_traits<std::complex<RealScalar>, RealScalar, UnitResIncr_, ConjLhs_, false, Arch, PacketSize_>
{
public:
typedef std::complex<RealScalar> LhsScalar;
@@ -756,8 +767,8 @@
// return res;
// }
-template<typename RealScalar, bool ConjLhs_, bool ConjRhs_, int Arch, int PacketSize_>
-class gebp_traits<std::complex<RealScalar>, std::complex<RealScalar>, ConjLhs_, ConjRhs_, Arch, PacketSize_ >
+template<typename RealScalar, bool UnitResIncr_, bool ConjLhs_, bool ConjRhs_, int Arch, int PacketSize_>
+class gebp_traits<std::complex<RealScalar>, std::complex<RealScalar>, UnitResIncr_, ConjLhs_, ConjRhs_, Arch, PacketSize_ >
{
public:
typedef std::complex<RealScalar> Scalar;
@@ -922,8 +933,8 @@
conj_helper<LhsScalar,RhsScalar,ConjLhs,ConjRhs> cj;
};
-template<typename RealScalar, bool ConjRhs_, int Arch, int PacketSize_>
-class gebp_traits<RealScalar, std::complex<RealScalar>, false, ConjRhs_, Arch, PacketSize_ >
+template<typename RealScalar, bool UnitResIncr, bool ConjRhs_, int Arch, int PacketSize_>
+class gebp_traits<RealScalar, std::complex<RealScalar>, UnitResIncr, false, ConjRhs_, Arch, PacketSize_ >
{
public:
typedef std::complex<RealScalar> Scalar;
@@ -1058,9 +1069,9 @@
template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
struct gebp_kernel
{
- typedef gebp_traits<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs,Architecture::Target> Traits;
- typedef gebp_traits<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs,Architecture::Target,GEBPPacketHalf> HalfTraits;
- typedef gebp_traits<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs,Architecture::Target,GEBPPacketQuarter> QuarterTraits;
+ typedef gebp_traits<LhsScalar,RhsScalar,DataMapper::incr == 1,ConjugateLhs,ConjugateRhs,Architecture::Target> Traits;
+ typedef gebp_traits<LhsScalar,RhsScalar,DataMapper::incr == 1,ConjugateLhs,ConjugateRhs,Architecture::Target,GEBPPacketHalf> HalfTraits;
+ typedef gebp_traits<LhsScalar,RhsScalar,DataMapper::incr == 1,ConjugateLhs,ConjugateRhs,Architecture::Target,GEBPPacketQuarter> QuarterTraits;
typedef typename Traits::ResScalar ResScalar;
typedef typename Traits::LhsPacket LhsPacket;
@@ -1071,7 +1082,7 @@
typedef typename RhsPanelHelper<RhsPacket, RhsPacketx4, 15>::type RhsPanel15;
- typedef gebp_traits<RhsScalar,LhsScalar,ConjugateRhs,ConjugateLhs,Architecture::Target> SwappedTraits;
+ typedef gebp_traits<RhsScalar,LhsScalar,DataMapper::incr == 1,ConjugateRhs,ConjugateLhs,Architecture::Target> SwappedTraits;
typedef typename SwappedTraits::ResScalar SResScalar;
typedef typename SwappedTraits::LhsPacket SLhsPacket;
@@ -1109,11 +1120,11 @@
};
template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs,
-int SwappedLhsProgress = gebp_traits<RhsScalar,LhsScalar,ConjugateRhs,ConjugateLhs,Architecture::Target>::LhsProgress>
+int SwappedLhsProgress = gebp_traits<RhsScalar,LhsScalar,DataMapper::incr == 1,ConjugateRhs,ConjugateLhs,Architecture::Target>::LhsProgress>
struct last_row_process_16_packets
{
- typedef gebp_traits<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs,Architecture::Target> Traits;
- typedef gebp_traits<RhsScalar,LhsScalar,ConjugateRhs,ConjugateLhs,Architecture::Target> SwappedTraits;
+ typedef gebp_traits<LhsScalar,RhsScalar,DataMapper::incr == 1,ConjugateLhs,ConjugateRhs,Architecture::Target> Traits;
+ typedef gebp_traits<RhsScalar,LhsScalar,DataMapper::incr == 1,ConjugateRhs,ConjugateLhs,Architecture::Target> SwappedTraits;
typedef typename Traits::ResScalar ResScalar;
typedef typename SwappedTraits::LhsPacket SLhsPacket;
@@ -1141,8 +1152,8 @@
template<typename LhsScalar, typename RhsScalar, typename Index, typename DataMapper, int mr, int nr, bool ConjugateLhs, bool ConjugateRhs>
struct last_row_process_16_packets<LhsScalar, RhsScalar, Index, DataMapper, mr, nr, ConjugateLhs, ConjugateRhs, 16> {
- typedef gebp_traits<LhsScalar,RhsScalar,ConjugateLhs,ConjugateRhs,Architecture::Target> Traits;
- typedef gebp_traits<RhsScalar,LhsScalar,ConjugateRhs,ConjugateLhs,Architecture::Target> SwappedTraits;
+ typedef gebp_traits<LhsScalar,RhsScalar,DataMapper::incr == 1,ConjugateLhs,ConjugateRhs,Architecture::Target> Traits;
+ typedef gebp_traits<RhsScalar,LhsScalar,DataMapper::incr == 1,ConjugateRhs,ConjugateLhs,Architecture::Target> SwappedTraits;
typedef typename Traits::ResScalar ResScalar;
typedef typename SwappedTraits::LhsPacket SLhsPacket;
@@ -1408,6 +1419,15 @@
Index rows, Index depth, Index cols, ResScalar alpha,
Index strideA, Index strideB, Index offsetA, Index offsetB)
{
+#if defined(EIGEN_VECTORIZE_AVX512)
+ if (nr == 8) {
+ bool done = gemm_kernel(
+ rows, cols, depth, alpha, blockA, blockB,
+ (ResScalar *)res.data(), res.stride(),
+ strideA, strideB, offsetA, offsetB);
+ if (done) return;
+ }
+#endif
Traits traits;
SwappedTraits straits;
@@ -2397,51 +2417,67 @@
Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
Index count = 0;
const Index peeled_k = (depth/PacketSize)*PacketSize;
-// if(nr>=8)
-// {
-// for(Index j2=0; j2<packet_cols8; j2+=8)
-// {
-// // skip what we have before
-// if(PanelMode) count += 8 * offset;
-// const Scalar* b0 = &rhs[(j2+0)*rhsStride];
-// const Scalar* b1 = &rhs[(j2+1)*rhsStride];
-// const Scalar* b2 = &rhs[(j2+2)*rhsStride];
-// const Scalar* b3 = &rhs[(j2+3)*rhsStride];
-// const Scalar* b4 = &rhs[(j2+4)*rhsStride];
-// const Scalar* b5 = &rhs[(j2+5)*rhsStride];
-// const Scalar* b6 = &rhs[(j2+6)*rhsStride];
-// const Scalar* b7 = &rhs[(j2+7)*rhsStride];
-// Index k=0;
-// if(PacketSize==8) // TODO enable vectorized transposition for PacketSize==4
-// {
-// for(; k<peeled_k; k+=PacketSize) {
-// PacketBlock<Packet> kernel;
-// for (int p = 0; p < PacketSize; ++p) {
-// kernel.packet[p] = ploadu<Packet>(&rhs[(j2+p)*rhsStride+k]);
-// }
-// ptranspose(kernel);
-// for (int p = 0; p < PacketSize; ++p) {
-// pstoreu(blockB+count, cj.pconj(kernel.packet[p]));
-// count+=PacketSize;
-// }
-// }
-// }
-// for(; k<depth; k++)
-// {
-// blockB[count+0] = cj(b0[k]);
-// blockB[count+1] = cj(b1[k]);
-// blockB[count+2] = cj(b2[k]);
-// blockB[count+3] = cj(b3[k]);
-// blockB[count+4] = cj(b4[k]);
-// blockB[count+5] = cj(b5[k]);
-// blockB[count+6] = cj(b6[k]);
-// blockB[count+7] = cj(b7[k]);
-// count += 8;
-// }
-// // skip what we have after
-// if(PanelMode) count += 8 * (stride-offset-depth);
-// }
-// }
+ if(nr>=8)
+ {
+ for(Index j2=0; j2<packet_cols8; j2+=8)
+ {
+ // skip what we have before
+ if(PanelMode) count += 8 * offset;
+ const LinearMapper dm0 = rhs.getLinearMapper(0, j2+0);
+ const LinearMapper dm1 = rhs.getLinearMapper(0, j2+1);
+ const LinearMapper dm2 = rhs.getLinearMapper(0, j2+2);
+ const LinearMapper dm3 = rhs.getLinearMapper(0, j2+3);
+ const LinearMapper dm4 = rhs.getLinearMapper(0, j2+4);
+ const LinearMapper dm5 = rhs.getLinearMapper(0, j2+5);
+ const LinearMapper dm6 = rhs.getLinearMapper(0, j2+6);
+ const LinearMapper dm7 = rhs.getLinearMapper(0, j2+7);
+ Index k=0;
+#if 0
+ // TODO Need to enable vectorized transposition.
+ if((PacketSize%8)==0) // TODO enable vectorized transposition for PacketSize==4
+ {
+ for(; k<peeled_k; k+=PacketSize) {
+ PacketBlock<Packet,(PacketSize%8)==0?8:PacketSize> kernel;
+
+ kernel.packet[0] = dm0.template loadPacket<Packet>(k);
+ kernel.packet[1] = dm1.template loadPacket<Packet>(k);
+ kernel.packet[2] = dm2.template loadPacket<Packet>(k);
+ kernel.packet[3] = dm3.template loadPacket<Packet>(k);
+ kernel.packet[4] = dm4.template loadPacket<Packet>(k);
+ kernel.packet[5] = dm5.template loadPacket<Packet>(k);
+ kernel.packet[6] = dm6.template loadPacket<Packet>(k);
+ kernel.packet[7] = dm7.template loadPacket<Packet>(k);
+
+ ptranspose(kernel);
+
+ pstoreu(blockB+count+0*PacketSize, cj.pconj(kernel.packet[0]));
+ pstoreu(blockB+count+1*PacketSize, cj.pconj(kernel.packet[1%PacketSize]));
+ pstoreu(blockB+count+2*PacketSize, cj.pconj(kernel.packet[2%PacketSize]));
+ pstoreu(blockB+count+3*PacketSize, cj.pconj(kernel.packet[3%PacketSize]));
+ pstoreu(blockB+count+4*PacketSize, cj.pconj(kernel.packet[4%PacketSize]));
+ pstoreu(blockB+count+5*PacketSize, cj.pconj(kernel.packet[5%PacketSize]));
+ pstoreu(blockB+count+6*PacketSize, cj.pconj(kernel.packet[6%PacketSize]));
+ pstoreu(blockB+count+7*PacketSize, cj.pconj(kernel.packet[7%PacketSize]));
+ count+=8*PacketSize;
+ }
+ }
+#endif
+ for(; k<depth; k++)
+ {
+ blockB[count+0] = cj(dm0(k));
+ blockB[count+1] = cj(dm1(k));
+ blockB[count+2] = cj(dm2(k));
+ blockB[count+3] = cj(dm3(k));
+ blockB[count+4] = cj(dm4(k));
+ blockB[count+5] = cj(dm5(k));
+ blockB[count+6] = cj(dm6(k));
+ blockB[count+7] = cj(dm7(k));
+ count += 8;
+ }
+ // skip what we have after
+ if(PanelMode) count += 8 * (stride-offset-depth);
+ }
+ }
if(nr>=4)
{
@@ -2522,39 +2558,50 @@
Index packet_cols4 = nr>=4 ? (cols/4) * 4 : 0;
Index count = 0;
- // if(nr>=8)
- // {
- // for(Index j2=0; j2<packet_cols8; j2+=8)
- // {
- // // skip what we have before
- // if(PanelMode) count += 8 * offset;
- // for(Index k=0; k<depth; k++)
- // {
- // if (PacketSize==8) {
- // Packet A = ploadu<Packet>(&rhs[k*rhsStride + j2]);
- // pstoreu(blockB+count, cj.pconj(A));
- // } else if (PacketSize==4) {
- // Packet A = ploadu<Packet>(&rhs[k*rhsStride + j2]);
- // Packet B = ploadu<Packet>(&rhs[k*rhsStride + j2 + PacketSize]);
- // pstoreu(blockB+count, cj.pconj(A));
- // pstoreu(blockB+count+PacketSize, cj.pconj(B));
- // } else {
- // const Scalar* b0 = &rhs[k*rhsStride + j2];
- // blockB[count+0] = cj(b0[0]);
- // blockB[count+1] = cj(b0[1]);
- // blockB[count+2] = cj(b0[2]);
- // blockB[count+3] = cj(b0[3]);
- // blockB[count+4] = cj(b0[4]);
- // blockB[count+5] = cj(b0[5]);
- // blockB[count+6] = cj(b0[6]);
- // blockB[count+7] = cj(b0[7]);
- // }
- // count += 8;
- // }
- // // skip what we have after
- // if(PanelMode) count += 8 * (stride-offset-depth);
- // }
- // }
+ if(nr>=8)
+ {
+ for(Index j2=0; j2<packet_cols8; j2+=8)
+ {
+ // skip what we have before
+ if(PanelMode) count += 8 * offset;
+ for(Index k=0; k<depth; k++)
+ {
+ if (PacketSize==8) {
+ // Packet A = ploadu<Packet>(&rhs.data()[k*rhs.stride() + j2]);
+ Packet A = rhs.template loadPacket<Packet>(k, j2);
+ pstoreu(blockB+count, cj.pconj(A));
+ } else if (HasHalf && HalfPacketSize==8) {
+ HalfPacket A = rhs.template loadPacket<HalfPacket>(k, j2);
+ pstoreu(blockB+count, cj.pconj(A));
+ } else if (HasQuarter && QuarterPacketSize==8) {
+ QuarterPacket A = rhs.template loadPacket<QuarterPacket>(k, j2);
+ pstoreu(blockB+count, cj.pconj(A));
+ } else if (PacketSize==4) {
+ // Packet A = ploadu<Packet>(&rhs.data()[k*rhs.stride() + j2]);
+ // Packet B = ploadu<Packet>(&rhs.data()[k*rhs.stride() + j2 + PacketSize]);
+ Packet A = rhs.template loadPacket<Packet>(k, j2);
+ Packet B = rhs.template loadPacket<Packet>(k, j2 + PacketSize);
+ pstoreu(blockB+count, cj.pconj(A));
+ pstoreu(blockB+count+PacketSize, cj.pconj(B));
+ } else {
+ // const Scalar* b0 = &rhs.data()[k*rhs.stride() + j2];
+ const LinearMapper dm0 = rhs.getLinearMapper(k, j2);
+ blockB[count+0] = cj(dm0(0));
+ blockB[count+1] = cj(dm0(1));
+ blockB[count+2] = cj(dm0(2));
+ blockB[count+3] = cj(dm0(3));
+ blockB[count+4] = cj(dm0(4));
+ blockB[count+5] = cj(dm0(5));
+ blockB[count+6] = cj(dm0(6));
+ blockB[count+7] = cj(dm0(7));
+ }
+ count += 8;
+ }
+ // skip what we have after
+ if(PanelMode) count += 8 * (stride-offset-depth);
+ }
+ }
+
if(nr>=4)
{
for(Index j2=packet_cols8; j2<packet_cols4; j2+=4)
diff --git a/Eigen/src/Core/products/GeneralMatrixMatrix.h b/Eigen/src/Core/products/GeneralMatrixMatrix.h
index 5262428..afd2e75 100644
--- a/Eigen/src/Core/products/GeneralMatrixMatrix.h
+++ b/Eigen/src/Core/products/GeneralMatrixMatrix.h
@@ -26,7 +26,7 @@
int ResInnerStride>
struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,RowMajor,ResInnerStride>
{
- typedef gebp_traits<RhsScalar,LhsScalar> Traits;
+ typedef gebp_traits<RhsScalar,LhsScalar,ResInnerStride == 1> Traits;
typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
static EIGEN_STRONG_INLINE void run(
@@ -57,7 +57,7 @@
struct general_matrix_matrix_product<Index,LhsScalar,LhsStorageOrder,ConjugateLhs,RhsScalar,RhsStorageOrder,ConjugateRhs,ColMajor,ResInnerStride>
{
-typedef gebp_traits<LhsScalar,RhsScalar> Traits;
+typedef gebp_traits<LhsScalar,RhsScalar, ResInnerStride == 1> Traits;
typedef typename ScalarBinaryOpTraits<LhsScalar, RhsScalar>::ReturnType ResScalar;
static void run(Index rows, Index cols, Index depth,
@@ -287,7 +287,6 @@
};
typedef std::conditional_t<Transpose,RhsScalar_,LhsScalar_> LhsScalar;
typedef std::conditional_t<Transpose,LhsScalar_,RhsScalar_> RhsScalar;
- typedef gebp_traits<LhsScalar,RhsScalar> Traits;
enum {
SizeA = ActualRows * MaxDepth,
SizeB = ActualCols * MaxDepth
@@ -336,7 +335,6 @@
};
typedef std::conditional_t<Transpose,RhsScalar_,LhsScalar_> LhsScalar;
typedef std::conditional_t<Transpose,LhsScalar_,RhsScalar_> RhsScalar;
- typedef gebp_traits<LhsScalar,RhsScalar> Traits;
Index m_sizeA;
Index m_sizeB;
diff --git a/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h b/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
index 716f2ca..b0024e7 100644
--- a/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
+++ b/Eigen/src/Core/products/GeneralMatrixMatrixTriangular.h
@@ -67,7 +67,7 @@
ResScalar* _res, Index resIncr, Index resStride,
const ResScalar& alpha, level3_blocking<LhsScalar,RhsScalar>& blocking)
{
- typedef gebp_traits<LhsScalar,RhsScalar> Traits;
+ typedef gebp_traits<LhsScalar,RhsScalar,ResInnerStride == 1> Traits;
typedef const_blas_data_mapper<LhsScalar, Index, LhsStorageOrder> LhsMapper;
typedef const_blas_data_mapper<RhsScalar, Index, RhsStorageOrder> RhsMapper;
@@ -140,7 +140,7 @@
template<typename LhsScalar, typename RhsScalar, typename Index, int mr, int nr, bool ConjLhs, bool ConjRhs, int ResInnerStride, int UpLo>
struct tribb_kernel
{
- typedef gebp_traits<LhsScalar,RhsScalar,ConjLhs,ConjRhs> Traits;
+ typedef gebp_traits<LhsScalar,RhsScalar,ResInnerStride == 1,ConjLhs,ConjRhs> Traits;
typedef typename Traits::ResScalar ResScalar;
enum {
diff --git a/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h b/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h
index 490fe67..66217e5 100644
--- a/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h
+++ b/Eigen/src/Core/products/GeneralMatrixMatrix_BLAS.h
@@ -55,7 +55,7 @@
int RhsStorageOrder, bool ConjugateRhs> \
struct general_matrix_matrix_product<Index,EIGTYPE,LhsStorageOrder,ConjugateLhs,EIGTYPE,RhsStorageOrder,ConjugateRhs,ColMajor,1> \
{ \
-typedef gebp_traits<EIGTYPE,EIGTYPE> Traits; \
+typedef gebp_traits<EIGTYPE,EIGTYPE,true> Traits; \
\
static void run(Index rows, Index cols, Index depth, \
const EIGTYPE* _lhs, Index lhsStride, \
diff --git a/Eigen/src/Core/products/SelfadjointMatrixMatrix.h b/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
index c7bb445..7c54787 100644
--- a/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
+++ b/Eigen/src/Core/products/SelfadjointMatrixMatrix.h
@@ -351,7 +351,7 @@
{
Index size = rows;
- typedef gebp_traits<Scalar,Scalar> Traits;
+ typedef gebp_traits<Scalar,Scalar,ResInnerStride == 1> Traits;
typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
typedef const_blas_data_mapper<Scalar, Index, (LhsStorageOrder == RowMajor) ? ColMajor : RowMajor> LhsTransposeMapper;
@@ -446,7 +446,7 @@
{
Index size = cols;
- typedef gebp_traits<Scalar,Scalar> Traits;
+ typedef gebp_traits<Scalar,Scalar,ResInnerStride == 1> Traits;
typedef const_blas_data_mapper<Scalar, Index, LhsStorageOrder> LhsMapper;
typedef blas_data_mapper<typename Traits::ResScalar, Index, ColMajor, Unaligned, ResInnerStride> ResMapper;
diff --git a/Eigen/src/Core/products/TriangularMatrixMatrix.h b/Eigen/src/Core/products/TriangularMatrixMatrix.h
index 770107a..6266dad 100644
--- a/Eigen/src/Core/products/TriangularMatrixMatrix.h
+++ b/Eigen/src/Core/products/TriangularMatrixMatrix.h
@@ -89,7 +89,7 @@
RhsStorageOrder,ConjugateRhs,ColMajor,ResInnerStride,Version>
{
- typedef gebp_traits<Scalar,Scalar> Traits;
+ typedef gebp_traits<Scalar,Scalar,ResInnerStride == 1> Traits;
enum {
SmallPanelWidth = 2 * plain_enum_max(Traits::mr, Traits::nr),
IsLower = (Mode&Lower) == Lower,
@@ -247,7 +247,7 @@
LhsStorageOrder,ConjugateLhs,
RhsStorageOrder,ConjugateRhs,ColMajor,ResInnerStride,Version>
{
- typedef gebp_traits<Scalar,Scalar> Traits;
+ typedef gebp_traits<Scalar,Scalar,ResInnerStride == 1> Traits;
enum {
SmallPanelWidth = plain_enum_max(Traits::mr, Traits::nr),
IsLower = (Mode&Lower) == Lower,
diff --git a/Eigen/src/Core/products/TriangularSolverMatrix.h b/Eigen/src/Core/products/TriangularSolverMatrix.h
index def6a28..2e6d6a8 100644
--- a/Eigen/src/Core/products/TriangularSolverMatrix.h
+++ b/Eigen/src/Core/products/TriangularSolverMatrix.h
@@ -189,7 +189,7 @@
TriMapper tri(_tri, triStride);
OtherMapper other(_other, otherStride, otherIncr);
- typedef gebp_traits<Scalar,Scalar> Traits;
+ typedef gebp_traits<Scalar,Scalar,OtherInnerStride == 1> Traits;
enum {
SmallPanelWidth = plain_enum_max(Traits::mr, Traits::nr),
@@ -336,7 +336,7 @@
LhsMapper lhs(_other, otherStride, otherIncr);
RhsMapper rhs(_tri, triStride);
- typedef gebp_traits<Scalar,Scalar> Traits;
+ typedef gebp_traits<Scalar,Scalar,OtherInnerStride == 1> Traits;
enum {
RhsStorageOrder = TriStorageOrder,
SmallPanelWidth = plain_enum_max(Traits::mr, Traits::nr),
diff --git a/Eigen/src/Core/util/BlasUtil.h b/Eigen/src/Core/util/BlasUtil.h
index f45665e..f59a55f 100755
--- a/Eigen/src/Core/util/BlasUtil.h
+++ b/Eigen/src/Core/util/BlasUtil.h
@@ -173,6 +173,7 @@
public:
typedef BlasLinearMapper<Scalar, Index, AlignmentType> LinearMapper;
typedef BlasVectorMapper<Scalar, Index> VectorMapper;
+ static constexpr int incr = 1;
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE blas_data_mapper(Scalar* data, Index stride, Index incr=1)
: m_data(data), m_stride(stride)
@@ -285,6 +286,7 @@
{
public:
typedef BlasLinearMapper<Scalar, Index, AlignmentType,Incr> LinearMapper;
+ static constexpr int incr = Incr;
EIGEN_DEVICE_FUNC EIGEN_ALWAYS_INLINE blas_data_mapper(Scalar* data, Index stride, Index incr) : m_data(data), m_stride(stride), m_incr(incr) {}
@@ -402,6 +404,9 @@
storePacketBlock_helper<SubPacket, Scalar, n, n-1> spb;
spb.store(this, i,j,block);
}
+
+ EIGEN_DEVICE_FUNC const Index stride() const { return m_stride; }
+ EIGEN_DEVICE_FUNC Scalar* data() const { return m_data; }
protected:
Scalar* EIGEN_RESTRICT m_data;
const Index m_stride;
diff --git a/unsupported/Eigen/MPRealSupport b/unsupported/Eigen/MPRealSupport
index c4ea4ec..8167bb1 100644
--- a/unsupported/Eigen/MPRealSupport
+++ b/unsupported/Eigen/MPRealSupport
@@ -143,8 +143,8 @@
// Specialize GEBP kernel and traits for mpreal (no need for peeling, nor complicated stuff)
// This also permits to directly call mpfr's routines and avoid many temporaries produced by mpreal
- template<>
- class gebp_traits<mpfr::mpreal, mpfr::mpreal, false, false>
+ template<bool UnitResIncr>
+ class gebp_traits<mpfr::mpreal, mpfr::mpreal, UnitResIncr, false, false>
{
public:
typedef mpfr::mpreal ResScalar;
