4 ms·

For decades the CPUs have been optimized to run faster existing applications - regardless in which programming languages the apps are written. On the other hand

by pulse7 6y ago

For decades the CPUs have been optimized to run faster existing applications - regardless in which programming languages the apps are written. On the other hand you can find languages designed around our CPUs (like Rust with its "zero-cost abstractions").

vbezhenar 6y ago
IMO the last language designed around CPU was C designed around CPUs of that time. Modern CPU have registers, caches, SIMD instructions which are tremendously important for performance. Yet I don't know no language which would explicitly provide any control over those things. You can only hope that your loop will be understood by compiler and optimized to proper SIMD instructions. And any change might break that optimization (including changes in compiler).
- dragontamer 6y ago
  > Yet I don't know no language which would explicitly provide any control over those things. CUDA provides your explicit cache control through "__shared__" memory. C commonly has low-level attributes. In particular, you have the "register" keyword in C if you really want to go that route, but compilers have a nice greedy algorithm that is damn near optimal, so its best to let the compiler perform its own analysis for register allocation. SIMD instructions are easily provided through intrinsics: https://software.intel.com/sites/landingpage/IntrinsicsGuide/ https://software.intel.com/sites/landingpage/IntrinsicsGuide... ------- There's plenty of low level languages that provide the control you desire. The main reason for __shared__ memory is that compilers can't optimize memory across threads yet, so we still require the programmer to tile memory manually and think about the optimizations across the many, many threads a CUDA multiprocessor supports. If you want to explicitly control the cache on x86 systems, use the _mm_prefetch() intrinsic. In practice though, it is pretty rare for prefetching to be useful on modern systems. (Auto-prefetchers will optimize most sequential traversals, and those that fail prefetching can still be out-of-order executed at decent speeds)

by pulse7 6y ago

vbezhenar 6y ago

IMO the last language designed around CPU was C designed around CPUs of that time. Modern CPU have registers, caches, SIMD instructions which are tremendously important for performance. Yet I don't know no language which would explicitly provide any control over those things. You can only hope that your loop will be understood by compiler and optimized to proper SIMD instructions. And any change might break that optimization (including changes in compiler).

dragontamer 6y ago
> Yet I don't know no language which would explicitly provide any control over those things. CUDA provides your explicit cache control through "__shared__" memory. C commonly has low-level attributes. In particular, you have the "register" keyword in C if you really want to go that route, but compilers have a nice greedy algorithm that is damn near optimal, so its best to let the compiler perform its own analysis for register allocation. SIMD instructions are easily provided through intrinsics: https://software.intel.com/sites/landingpage/IntrinsicsGuide/ https://software.intel.com/sites/landingpage/IntrinsicsGuide... ------- There's plenty of low level languages that provide the control you desire. The main reason for __shared__ memory is that compilers can't optimize memory across threads yet, so we still require the programmer to tile memory manually and think about the optimizations across the many, many threads a CUDA multiprocessor supports. If you want to explicitly control the cache on x86 systems, use the _mm_prefetch() intrinsic. In practice though, it is pretty rare for prefetching to be useful on modern systems. (Auto-prefetchers will optimize most sequential traversals, and those that fail prefetching can still be out-of-order executed at decent speeds)